Instructions to use debisoft/Qwen3-8B-thinking-function_calling-quant-V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use debisoft/Qwen3-8B-thinking-function_calling-quant-V0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("debisoft/Qwen3-8B-thinking-function_calling-quant-V0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e89bc4632bc02fe6c9927b476f4cb52d655abcfd68f79a81fcdbefa7d19afec7
- Size of remote file:
- 5.69 kB
- SHA256:
- b29168863c061a15f58073546e4e3fe270cd7c9b993d70e1b7ce75b943e35ef1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.